ArticleNature human behaviour2023
Sensory perception relies on fitness-maximizing codes.
Article in Nature human behaviour, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Intrinsic rewards guide visual resource allocation via reinforcement learning.Nature human behaviour · 2026Article
- Endogenous precision of the number sense.eLife · 2026Article
- The Impact of Action Intention Versus Action-Effect Intention on Auditory Prediction Error Signals.The European journal of neuroscience · 2026Article
- Engaging with uncertainty when engagement is uncertain.Frontiers in bioinformatics · 2026Article
- Discovery of the reward function for embodied reinforcement learning agents.Nature communications · 2025Article
- Blaming luck, claiming skill: Self-attribution bias in error assignment.PLoS computational biology · 2025Article
- Approach-avoidance conflict recruits lateral frontoparietal and cinguloinsular networks in a predator-prey game setting.Cognitive, affective & behavioral neuroscience · 2025Article
- Decoding olfactory bulb output: A behavioral assessment of rate, synchrony, and respiratory phase coding.iScience · 2025Article
- The geometry of efficient codes: How rate-distortion trade-offs distort the latent representations of generative models.PLoS computational biology · 2025Article
- Efficient numerosity estimation under limited time.PLoS computational biology · 2025Article
- Context changes retrieval of prospective outcomes during decision deliberation.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Jointly efficient encoding and decoding in neural populations.PLoS computational biology · 2024Article
- Whole-brain responses to visual and auditory stimuli in anesthetized and minimally restrained awake mice using quiet zero echo time fMRI.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- The maps of meaning consciousness theory.Frontiers in psychology · 2024Article
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5 authors.
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Abstract
Sensory information encoded by humans and other organisms is generally presumed to be as accurate as their biological limitations allow. However, perhaps counterintuitively, accurate sensory representations may not necessarily maximize the organism's chances of survival. To test this hypothesis, we developed a unified normative framework for fitness-maximizing encoding by combining theoretical insights from neuroscience, computer science, and economics. Behavioural experiments in humans revealed that sensory encoding strategies are flexibly adapted to promote fitness maximization, a result confirmed by deep neural networks with information capacity constraints trained to solve the same task as humans. Moreover, human functional MRI data revealed that novel behavioural goals that rely on object perception induce efficient stimulus representations in early sensory structures. These results suggest that fitness-maximizing rules imposed by the environment are applied at early stages of sensory processing in humans and machines.
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